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## llm-wiki.md

      
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                karpathy
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                llm-wiki
              
          
    LLM Wiki

A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

  
## Dark Souls II Cheat Engine Guide.md

      
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                Atvaark
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    Dark Souls II and Scholar of the First Sin Cheat Engine Guide

Updates

04/05/2020


Added HP Min Offset
Added “Replenishment [Phantom Color]” from previous tables versions (not made by me)
Mapped some offsets for easier reading
Added offset +74 (Parry Multiplier) under [Equipped Weapon]
Added WeaponTypeParam Helper


## mtp-bench.py
#!/usr/bin/env python3
import argparse, json, sys, time
from urllib import request

PROMPTS = [
    {"name": "code_python",      "prompt": "Write a Python function that returns the n-th Fibonacci number using memoization. Include a docstring."},
    {"name": "code_cpp",         "prompt": "Write a C++ template function `clamp(x, lo, hi)` that returns x clamped to [lo, hi]. No std::clamp."},
    {"name": "explain_concept",  "prompt": "Explain how speculative decoding works in large language model inference, in three short paragraphs."},
    {"name": "summarize",        "prompt": "Summarize in two sentences: The Industrial Revolution began in Britain in the late 18th century, transforming manufacturing through mechanization, steam power, and the factory system. It spread to continental Europe and North America during the 19th century."},
    {"name": "qa_factual",       "prompt": "Q: What are the four fundamental forces of physics?\nA:"},

## how-to-continue.md

      
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    How to continue?

This a curate guide to continue your preparation for technical coding interviews, with resources, tips, and practice problems organized by topic. Enjoyed 🙌
📚 Additional Resources

Online Platforms


LeetCode - The most popular platform for coding interview prep. Start with their "Top Interview Questions" collections.
NeetCode - Curated list of 150 best LeetCode problems with video explanations.
GeeksforGeeks - Comprehensive explanations and problems for every data structure and algorithm.


## SKILL.md

      
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                aparente
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                tufte-viz Claude Code skill — Edward Tufte data visualization principles
              
          
name: tufte-viz
description: |
Ideate and critique data visualizations using Edward Tufte's principles from "The Visual Display of Quantitative Information." Use this skill when:
(1) Designing new data visualizations or charts
(2) Critiquing or improving existing visualizations
(3) Reviewing dashboards or reports for graphical integrity
(4) Deciding between visualization approaches
(5) Reducing chartjunk or improving data-ink ratio
(6) Planning small multiples or high-density displays

  
## channels.go
package main

import (
	"fmt"
	"sync"
	"sync/atomic"
)

// Fill Channel with int values
func fillChan(number int) <-chan int {

## cgp.md

      
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                notnotrobby
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                List of free resources to study computer graphics programming.
              
          
    Computer Graphics Programming Resources

List of freely available resources to study computer graphics programming.
Table of Contents


Basic Path
Getting Started
C++
Mathematics
Overview


## IPA-Sources.md

      
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                ongkiii
                / IPA-Sources.md
            
            
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                REPOS/TELEGRAM CHANNELS LIST BY u/angkitbharadwaj
              
          
🗂️ REPOS/TELEGRAM CHANNELS LIST

By u/angkitbharadwaj


Visit fmhy.net/android-iosguide#ios-ipas for more sources.
Sideloading Guide: https://rentry.co/sideloadingguide, https://ios.cfw.guide/sideloading-apps/


## gist:a64010915eccda2ccaa527199bcfd323
# Workflow Orchestration

## 1. Plan Mode Default

- Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
- If something goes sideways, STOP and re-plan immediately — don't keep pushing
- Use plan mode for verification steps, not just building
- Write detailed specs upfront to reduce ambiguity

## 2. Subagent Strategy
	#!/usr/bin/env python3
	import argparse, json, sys, time
	from urllib import request

	PROMPTS = [
	{"name": "code_python", "prompt": "Write a Python function that returns the n-th Fibonacci number using memoization. Include a docstring."},
	{"name": "code_cpp", "prompt": "Write a C++ template function `clamp(x, lo, hi)` that returns x clamped to [lo, hi]. No std::clamp."},
	{"name": "explain_concept", "prompt": "Explain how speculative decoding works in large language model inference, in three short paragraphs."},
	{"name": "summarize", "prompt": "Summarize in two sentences: The Industrial Revolution began in Britain in the late 18th century, transforming manufacturing through mechanization, steam power, and the factory system. It spread to continental Europe and North America during the 19th century."},
	{"name": "qa_factual", "prompt": "Q: What are the four fundamental forces of physics?\nA:"},
	package main

	import (
	"fmt"
	"sync"
	"sync/atomic"
	)

	// Fill Channel with int values
	func fillChan(number int) <-chan int {
	# Workflow Orchestration

	## 1. Plan Mode Default

	- Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
	- If something goes sideways, STOP and re-plan immediately — don't keep pushing
	- Use plan mode for verification steps, not just building
	- Write detailed specs upfront to reduce ambiguity

	## 2. Subagent Strategy